• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.709-712
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• 1996

Generating a project network of a specific construction project is very time consuming and difficult task in the field. To effectiviely automate and support the planning process, we design a case-based project planning expert system inspired by the fact a human expert project planner uses previous cases for planning a new project. A construction project case consist of its specific characteristics and the corresponding project network (i.e. project plan). Using frame based representation. we represent the project features affecting the progress network and the entities composing the project plan such as the buildings, construction methods, WBS (work breakdown structure), activities, and resources. The project planning process runs through most similar case retrieval, case adaptation, and user requirement satisfaction. We represent the construction domain knowledge for each procedure using constraints and rules. We develop the methodology for constraint-based case adaption. Case adaptation process mainly consist of activity generation/deletion and predecence constraint satisfaction, for which we develop the dynamic constraint generation method and connect user-level requirement representation the system-level network modification knowledge. The methodology is being applied to the prototype for apartment construction project planning.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.491-493
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• 2011

Traffic sign detection is the domain of automatic driver assistant systems. There are literatures for traffic sign detection using color information, however, color-based method contains ill-posed condition and to extract the region of interest is difficult. In our work, we propose a method for traffic sign detection using k-means clustering method, back-propagation neural network, and projection histogram features that yields the robustness for ill-posed condition. Using the color information of traffic signs enables k-means algorithm to cluster the region of interest for the detection efficiently. In each step of clustering, a cluster is verified by the neural network so that the cluster exactly represents the location of a traffic sign. Proposed method is practical, and yields robustness for the unexpected region of interest or for multiple detections.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2009-2010
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• 2006

This paper presents an adaptive line coupler to match input impedance of the Power line Communication(PLC) modem between access impedance of the power line. This line coupler provides maximum signal power transmiting capability, high reliability. The structure of this coupler is simple and designed to make a easy and low cost. The proposed line coupler is suitable for Amplitude Shift Keying(ASK) or Phase Shift Keying(PSK) modem. To figure out our models, the analysis of the transmitting features of power line channel is performed in the time domain at the carrier frequency. As a result of this study, we present the values of capacitors in the capacitor bank and adaptive line coupler circuit.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.151-154
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• 2002

The objective of this study is to find the change of signal characteristics of matrix cracks due to the different specimen shapes. As the concept of the smart structure, monitoring of acoustic emission (AE) can be applied to inspect the fracture of the structures in operating condition using built-in sensors. To understand the characteristics of matrix crack signals, we performed tensile tests by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as wavelet transform (WT) fur the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.635-640
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• 2001

This paper introduces a frequency-domain method of structural damage identification. It is formulated in a general form from the dynamic stiffness equation of motion for a structure and then applied to a beam structure. The appealing features of the present damage identification method are: (1) it requires only the frequency response functions experimentally measured from damaged structure as the input data, and (2) it can locate and quantify many local damages at the same time. The feasibility of the present damage identification method is tested through some numerically simulated damage identification analyses and then experimental verification is conducted for a cantilevered beam with damage caused by introducing three slots.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.366-373
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• 2003

This paper introduces a frequency-domain method of structural damage identification. It is formulated in a general form to include the nonlinearity of damage magnitudes from the dynamic stiffness equation of motion for a beam structure. The appealing features of the present damage identification method are: (1) it requires only the frequency response functions measured from damaged structure as the input data, and (2) it can locate and quantify many local damages at the same time. The feasibility of the present damage identification method is tested through some numerically simulated damage identification analyses for a cantilevered beam with three piece-wise uniform damages.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1133-1138
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• 2000

This paper describes a signal recognition method for diagnosing the rotating machinery using wavelet-aided Self-Organizing Feature Map(SOFM). The SOFM specialized from neural network is a new and effective algorithm for interpreting large and complex data sets. It converts high-dimensional data items into simple order relationships with low dimension. Additionally the Learning Vector Quantization(LVQ) is used for reducing the error from SOFM. Multi-resolution and wavelet transform are used to extract salient features from the primary vibration signals. Since it decomposes the raw timebase signal into two respective parts in the time space and frequency domain, it does not lose either information unlike Fourier transform. This paper is focused on the development of advanced signal classifier in order to automatize vibration signal pattern recognition. This method is verified by the experiment and several abnormal vibrations such as unbalance and rubbing are classified with high flexibility and reliability by the proposed methods.

• Wind and Structures
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• v.31 no.5
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• pp.459-472
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• 2020

This study focused on the non-synoptic, tornado-like wind-induced effects on flexible horizontal structures that are extremely sensitive to winds. More specifically, the nonuniform, intensive vertical wind-velocity and transient natures of tornado events and their effects on the global behavior of a long-span bridge were investigated. In addition to the static part in the modeling of tornado-like wind-induced loads, the motion-induced effects were modeled using the semi-empirical model with a two-dimensional (2-D) indicial response function. Both nonlinear wind-induced static analysis and linear aeroelastic analysis in the time domain were conducted based on a 3-D finite-element model to investigate the bridge performance under the most unfavorable tornado pattern considering wind-structure interactions. The results from the present study highlighted the important effects due to abovementioned tornado natures (i.e., nonuniform, intensive vertical wind-velocity and transient features) on the long-span bridge, and hence may facilitate more appropriate wind design of flexible horizontal structures in the tornado-prone areas.

• Journal of the Korean Society of Combustion
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• v.22 no.3
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• pp.41-46
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• 2017

This study has numerically investigated the flame-acoustics interactions in the turbulent partially premixed flame field. In the present approach, in order to analyze the combustion instability, the present approach has employed the LES-based combustion model as well as the Helmholtz solver. Computations are made for the validation case of the partially premixed LIMOUSINE burner. In terms of the FFT data, numerical results are compared with experimental data. Moreover, Helmholtz equation in frequency domain is solved by combining CFD field data including the flight time from a nozzle to the flame zone. Based on numerical results, the detailed discussions are made for the essential features of the combustion instability encountered in the partially premixed burner.